Design of GAmut-Lssahc: a solver for course timetabling problem
M. Nandhini and
S. Kanmani
International Journal of Mathematics in Operational Research, 2011, vol. 3, issue 6, 595-618
Abstract:
In this paper, the problem of course timetabling is studied extensively and its constraints are represented using mathematical representation. Analysing the existing GA-based methodologies for solving University Course Timetabling problem, a new method has been proposed probably, which has not yet been attempted for this problem. It employs GA with a variety of proposed MUTation operators (Random-Selection; Adaptive; Goal-Directed) and Local Search of Steepest Ascent Hill Climbing (GAmut-LSsahc) to increase the fitness value and could produce optimal course timetable at the earliest. It was experimentally proved that goal-directed converges 6% faster than adaptive and 10% faster than random-selection mutation.
Keywords: combinatorial problems; feasibility; genetic algorithms; GAs; mutation; optimisation; steepest ascent hill climbing; course timetabling; course timetables. (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=43012 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmore:v:3:y:2011:i:6:p:595-618
Access Statistics for this article
More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().